Despite large progress in Explainable and Safe AI, practitioners suffer ...
Manual assembly workers face increasing complexity in their work.
Human-...
Being able to predict the remaining useful life (RUL) of an engineering
...
In recent years, the development of Artificial Intelligence (AI) has sho...
When it comes to the optimization of CAD models in the automation domain...
Data-hunger and data-imbalance are two major pitfalls in many deep learn...
This work introduces a novel interpretable machine learning method calle...
Our goal in this paper is to automatically extract a set of decision rul...
In the last ten years, various automated machine learning (AutoML) syste...
In the domain of computer vision, deep residual neural networks like
Eff...
Human activity recognition is seen of great importance in the medical an...
Radar for deep learning-based human identification has become a research...
This paper introduces a novel approach for the grasping and precise plac...
Compared to point estimates calculated by standard neural networks, Baye...
Maintenance scheduling is a complex decision-making problem in the produ...
Convolutional Neural Networks (CNN) have become de fact state-of-the-art...
Lower extremity amputees face challenges in natural locomotion, which is...
This paper presents a novel approach for the automatic offline grasp pos...
Single shot approaches have demonstrated tremendous success on various
c...
Automated machine learning (AutoML) aims for constructing machine learni...
In this paper, we introduce a novel learning-based approach for grasping...
Predictions obtained by, e.g., artificial neural networks have a high
ac...
Artificial neural networks (NNs) have become the de facto standard in ma...
In this paper, we introduce a novel single shot approach for 6D object p...
In this paper, we introduce a new public dataset for 6D object pose
esti...
For most industrial bin picking solutions, the pose of a workpiece is
lo...
Machine learning has become a vital part in many aspects of our daily li...
One obstacle that so far prevents the introduction of machine learning m...
We propose a principled algorithm for robust Bayesian filtering and smoo...